10 Questions How do we secure the data used to train our models — and ensure it hasn’t been poisoned or manipulated 

Instructions

Answer the following questions to assess understanding of data security and data poisoning prevention in AI model training.

Securing training data is essential to ensure AI models behave reliably. Organizations must verify data integrity, restrict access, detect anomalies, and validate sources to prevent data poisoning, where attackers insert manipulated or malicious data to influence model behavior. Strong governance, monitoring, and cryptographic verification help ensure data remains trustworthy. 

 

Results

#1. Data poisoning occurs when:

A. A model is trained on too much data

B. An attacker manipulates training data to influence model behavior

C. Data is stored in the cloud

D. A model is updated too frequently

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